CITEViz 1.0
CITEViz (pronounced “CITE-Viz”) is a single-cell visualization platform with a custom module that replicates the flow-cytometry gating workflow. In real time, users can iteratively subset cell populations of interest using the unique surface proteins, and see those cells reflected in the original dimension reduction (e.g. PCA, tSNE, UMAP) space (forward-gate). Users can also highlight cells in dimensional reduction (DR) space and quickly locate them in a 2D gate window via back-gating. Additionally, CITEViz provides interactive quality control (QC) plots and 2D multi-omic feature expression plots. This vignette demonstrates the usage of CITEViz on a subset of CITE-seq data from peripheral blood mononuclear cells by Hao et. al. 2021.
Make sure you have R version 4.1.0 or later installed. We recommend installing CITEViz through the RStudio IDE using the following commands:
devtools::install_github("maxsonBraunLab/CITEViz")
library(CITEViz)
run_app()
CITEViz will be uploaded to Bioconductor version 3.16, and the release date is currently set for October 2022.
CITEViz accepts files in the RDS (.rds) format. Files should include a Seurat object or list of Seurat objects, with each object representing an experimental sample or treatment condition. Alternatively, a single Seurat object containing data integrated from all treatment conditions (an “integrated” object) can be used. A file can be uploaded using the depicted file upload box at the top of any page in CITEViz, and the same dataset will be retained for exploration across all tabs.
The first step of analysis is to assess the quality of sequencing data. Here we provide QC plots that display data for common metrics such as gene or antibody-derived tag (ADT) counts per assay, number of unique ADTs, and mitochondrial expression, which can be visualized by any categorical metadata in the user’s Seurat object.
The Clustering page allows the user to view cell clusters in two- and three-dimensional space. These clusters can be colored by any categorical metadata, and the user can select dimensionality reductions (e.g., UMAP, PCA, etc.) to view from a dropdown menu. When the user’s cursor hovers over the 2D reduction plot, a plot toolbox with labeled options will appear. From this toolbox, the user can zoom, pan, download, and reset a plot by selecting an option. The user can also use the box or lasso selection tool to select specific cells in a plot. The metadata for selected cells appears in the data table below the plots, and the user can print or copy this data to their clipboard.